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3D object detection has seen quick progress thanks to advances in deep learning on point clouds.
Machine analysis of bubble chamber pictures
Paul VC Hough · 1959
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Generalizing the hough transform to detect arbitrary shapes
Dana H Ballard · 1981
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Affine structure from motion
Jan J Koenderink and Andrea J Van Doorn · 1991
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Visual odometry
David Nistér, Oleg Naroditsky, and James Bergen · 2004
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Orb: An efficient alternative to sift or surf
Ethan Rublee, Vincent Rabaud, Kurt Konolige, and Gary R Bradski · 2011
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A search-classify approach for cluttered indoor scene understanding
Liangliang Nan, Ke Xie, and Andrei Sharf · 2012
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Indoor segmentation and support inference from rgbd images
Nathan Silberman, Derek Hoiem, Pushmeet Kohli, and Rob Fergus · 2012
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A category-level 3d object dataset: Putting the kinect to work
Allison Janoch, Sergey Karayev, Yangqing Jia, Jonathan T Barron, Mario Fritz, Kate Saenko, and Trevor Darrell · 2013
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Sun3d: A database of big spaces reconstructed using sfm and object labels
Jianxiong Xiao, Andrew Owens, and Antonio Torralba · 2013
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Sliding shapes for 3d object detection in depth images
Shuran Song and Jianxiong Xiao · 2014
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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh · 2015
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Database-assisted object retrieval for real-time 3d reconstruction
Yangyan Li, Angela Dai, Leonidas Guibas, and Matthias Nießner · 2015
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Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Sun rgb-d: A rgb-d scene understanding benchmark suite
Shuran Song, Samuel P Lichtenberg, and Jianxiong Xiao · 2015
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Data-driven structural priors for shape completion
Minhyuk Sung, Vladimir G Kim, Roland Angst, and Leonidas Guibas · 2015
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Multimodal compact bilinear pooling for visual question answering and visual grounding
Akira Fukui, Dong Huk Park, Daylen Yang, Anna Rohrbach, Trevor Darrell, and Marcus Rohrbach · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Ssd: Single shot multibox detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C Berg · 2016
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Visually indicated sounds
Andrew Owens, Phillip Isola, Josh McDermott, Antonio Torralba, Edward H Adelson, and William T Freeman · 2016
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Ambient sound provides supervision for visual learning
Andrew Owens, Jiajun Wu, Josh H McDermott, William T Freeman, and Antonio Torralba · 2016
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You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
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Three-dimensional object detection and layout prediction using clouds of oriented gradients
Zhile Ren and Erik B Sudderth · 2016
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Deep sliding shapes for amodal 3d object detection in rgb-d images
Shuran Song and Jianxiong Xiao · 2016
Deep continuous fusion for multi-sensor 3d object detection
Ming Liang, Bin Yang, Shenlong Wang, and Raquel Urtasun · 2018
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Film: Visual reasoning with a general conditioning layer
Ethan Perez, Florian Strub, Harm De Vries, Vincent Dumoulin, and Aaron Courville · 2018
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Frustum pointnets for 3d object detection from rgb-d data
Charles R Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J Guibas · 2018
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Pointrcnn: 3d object proposal generation and detection from point cloud
Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2018
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Pointfusion: Deep sensor fusion for 3d bounding box estimation
Danfei Xu, Dragomir Anguelov, and Ashesh Jain · 2018
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Gspn: Generative shape proposal network for 3d instance segmentation in point cloud
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Cited alongside, same era.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
Cited alongside, same era.
Amodal detection of 3d objects: Inferring 3d bounding boxes from 2d ones in rgb-depth images
Zhuo Deng and Longin Jan Latecki · 2017
Cited alongside, same era.
Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Li Fei-Fei, C Lawrence Zitnick, and Ross Girshick · 2017
Cited alongside, same era.
2d-driven 3d object detection in rgb-d images
Jean Lahoud and Bernard Ghanem · 2017
Cited alongside, same era.
Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
Cited alongside, same era.
Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
Cited alongside, same era.
Li Yi, Wang Zhao, He Wang, Minhyuk Sung, and Leonidas Guibas · 2018
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Beyond bilinear: Generalized multimodal factorized high-order pooling for visual question answering
Zhou Yu, Jun Yu, Chenchao Xiang, Jianping Fan, and Dacheng Tao · 2018
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The sound of pixels
Hang Zhao, Chuang Gan, Andrew Rouditchenko, Carl Vondrick, Josh McDermott, and Antonio Torralba · 2018
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Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
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Scan2cad: Learning cad model alignment in rgb-d scans
Armen Avetisyan, Manuel Dahnert, Angela Dai, Manolis Savva, Angel X. Chang, and Matthias Nießner · 2019
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4d spatio-temporal convnets: Minkowski convolutional neural networks
Christopher Choy, JunYoung Gwak, and Silvio Savarese · 2019
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2.5 d visual sound
Ruohan Gao and Kristen Grauman · 2019
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3d-sis: 3d semantic instance segmentation of rgb-d scans
Ji Hou, Angela Dai, and Matthias Nießner · 2019
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Pointpillars: Fast encoders for object detection from point clouds
Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
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Deep hough voting for 3d object detection in point clouds
Charles R. Qi, Or Litany, Kaiming He, and Leonidas J. Guibas · 2019
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Densefusion: 6d object pose estimation by iterative dense fusion
Chen Wang, Danfei Xu, Yuke Zhu, Roberto Martín-Martín, Cewu Lu, Li Fei-Fei, and Silvio Savarese · 2019
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What makes training multi-modal networks hard?
Weiyao Wang, Du Tran, and Matt Feiszli · 2019
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